Preliminary Results from a Field Experiment of Three Fuel Economy Feedback Designs

Energy feedback to drivers is one method to engage drivers in energy saving driving styles. In contrast to the occasional broadcasting of general driving tips, in-vehicle energy feedback gives drivers access to accurate information about their specific driving situation on an ongoing basis. The increasing prevalence of such feedback in new vehicles suggests a belief that ongoing, in-vehicle feedback is better. However, there is little reliable evidence of the effectiveness of energy feedback in real-word driving in passenger vehicles. This study begins to fill this gap. Participants are given a commercially available fuel consumption display and recording device to use in their personal vehicle for two months. For the first month the display is blank as the device records a baseline of driving and fuel consumption. For the second month the display is switched on to show drivers one of three feedback designs. This paper presents preliminary results (N=36) of a larger study that will include 150 drivers along the California-Nevada Interstate-80 corridor. Using a mixed-effects linear model, an average decrease of 13 between 2% and 8% in fuel consumption (gallons/100 miles) between the without- and with-feedback months, depending on the feedback designs, is found. Categorizing trips into types based on distance and multiple speed characteristics, there are differences in the apparent effectiveness of feedback across trip types. Most trips average approximately 5% reduction in fuel consumption. The long distance highway trip type showed only a 1% decrease in fuel consumption between the two study periods

Goal Setting, Framing, and Anchoring Responses to Ecodriving Feedback

Ecodriving, defined here as the adoption of energy efficient driving styles and practices (primarily moderating acceleration, top speed, increased coasting, and improved maintenance practices), has long been recognized as a potential source of reductions in transportation energy use. Estimates of energy savings attributed to ecodriving range widely, from less than 5% to as high as 20% depending on the driving and experimental context. To explore the effects on ecodriving of interaction between drivers and in-vehicle energy feedback, a customized, interactive energy feedback interface was deployed in a field test with real-world drivers. This paper presents the results of interviews with 46 Plug-in Hybrid Electric Vehicle (PHEV) drivers who were given the ecodriving feedback interface for a multi-week trial including an interface off (baseline) and on (treatment) condition. This paper relies specifically on self-reports of driver motivations and behaviors to better understand what types of information motivated new ecodriving behavior; a future paper will investigate quantitative fuel consumption effects. Driver interviews at the conclusion of the study revealed that the introduction of feedback led three fourths of drivers to change driving styles to maximize on-road efficiency, at least in the short term. In addition, this study finds that the context of the feedback information, provided by a built-in goal or other contextualizing information such as a comparison value, is important for both comprehension and motivation. Personalization of the information allowed different drivers to access pertinent information, increasing the motivational value of the information. Instantaneous performance feedback such as real-time energy economy or power is used primarily for experimentation and learning of new ecodriving behaviors, whereas average performance feedback is used primarily for goal-setting and goal achievement. In addition, the direct comparison of personalized driver goals and average performance created a game-like experience that encouraged high achievement. Finally, the driver interviews revealed that feedback frames driving as a time to act in an efficient manner

Cognitive Mechanisms of Behavior Change in the Case of In-Vehicle Fuel Economy Feedback

This paper presents results from a year-long study on driver feedback, driver attitudes, and the adoption of ecodriving behaviors. Narrowly defined, ecodriving represents only the set of behaviors that a driver can use to minimize the energy use of a trip after the trip has begun. The general ecodriving behaviors are moderating acceleration, top speed, and braking. Ecodriving has long been recognized as a potential source of reductions in transportation energy use, with reduction estimates ranging widely from less than 5% to over 20% depending on context. In-vehicle feedback is one way to motivate ecodriving by connecting drivers with salient information suited to their personal goals. Although many studies have tested unique feedback designs, little research has been conducted into the cognitive precursors to driver behavior change that may underlie the adoption or rejection of ecodriving practices, and therefore underlie the effectiveness of any feedback design. This study examines both precursor cognitive factors and driver behavior changes with the introduction of energy feedback, using a framework hypothesizing that attitudes, social norms, perceived control, and goals influence behavior and behavior change. The study finds that the introduction of a feedback interface can both activate these cognitive factors and result in behavior change. Furthermore, the study finds that there was an overall 4.4% reduction in fuel consumption due entirely to one group that showed increases in their knowledge of fuel economy and reported high levels of technical proficiency during the experiment. The second group made no improvement and may have been confused by the feedback. In addition, statistically significant relationships are found in the effective group between the magnitude of cognitive change and the magnitude of behavior change – supporting the theoretical framework. Finally, the baseline (prefeedback) performance of the drivers was an important model factor, indicating that drivers that already use highly efficient styles do not benefit much from feedback

Comprehending Consumption: The Behavioral Basis and Implementation of Driver Feedback for Reducing Vehicle Energy Use

By easily comprehending their own energy consumption, individuals can make both individually and socially responsible choices. How and when that potential translates into actual choices is explored, first by using mile-per-gallon fuel economy as a metric for driver feedback and finding that the metric is unable to transmit accurate information about the impact of driving style on energy use. An alternative energy economy metric, the theory of planned behavior, is tested against driver responses to an existing feedback system available in the 2008 model Toyota Prius. It appears that driver responses support the use of behavioral theories to both measure and design feedback systems. A novel feedback design based on behavioral theories and drivers' responses to the feedback is presented. The quantitative results of a year long study of fuel economy in response to feedback finds the novel feedback design generates a statistically significant increase in fuel economy overall. The feedback also influences drivers' goals and attitudes. This finding supports the underlying behavioral theory and suggests that energy related behavioral decisions are dependent on the quality and behavioral relevance of information that people have about their choices and the resulting consequences

Comprehending Consumption: The Behavioral Basis and Implementation of Driver Feedback for Reducing Vehicle Energy Use

A large body of evidence suggests that drivers who receive real-time fuel economy information can increase their vehicle fuel economy by 5%, a process commonly known as ecodriving. However, few studies have directly addressed the human side of the feedback, that is, why drivers would (or would not) be motivated to change their behavior and how to design feedback devices to maximize the motivation to ecodrive. This dissertation approaches the question using a mixed qualitative and quantitative approach to explore driver responses and psychology as well as to quantify the process of behavior change. The first chapter discusses the use of mile-per-gallon fuel economy as a metric for driver feedback and finds that an alternative energy economy metric is superior for real-time feedback. The second chapter reviews behavioral theories and proposes a number of practical solutions for the ecodriving context. In the third chapter the theory of planned behavior is tested against driver responses to an existing feedback system available in the 2008 model Toyota Prius. The fourth chapter presents a novel feedback design based on behavioral theories and drivers' responses to the feedback. Finally, chapter five presents the quantitative results of a natural-driving study of fuel economy feedback. The dissertation findings suggest that behavior theories such as the Theory of Planned Behavior can provide important improvements to existing feedback designs. In addition, a careful analysis of vehicle energy flows indicates that the mile-per-gallon metric is deeply flawed as a real-time feedback metric, and should be replaced. Chapters 2 and 3 conclude that behavior theories have both a theoretical and highly practical role in feedback design, although the driving context requires just as much care in the application. Chapters 4 and 5 find that a theory-inspired interface provides drivers with engaging and motivating feedback, and that integrating personal goal into the feedback is the most motivating theory-based addition. Finally, the behavioral model results in chapter 5 suggest that driver goals not only influence in-vehicle energy use, but are themselves flexible constructs that can be directly influenced by energy feedback

Preliminary Results from a Field Experiment of Three Fuel Economy Feedback Designs

Energy feedback to drivers is one method to engage drivers in energy saving driving styles. In contrast to the occasional broadcasting of general driving tips, in-vehicle energy feedback gives drivers access to accurate information about their specific driving situation on an ongoing basis. The increasing prevalence of such feedback in new vehicles suggests a belief that ongoing, in-vehicle feedback is better. However, there is little reliable evidence of the effectiveness of energy feedback in real-word driving in passenger vehicles. This study begins to fill this gap. Participants are given a commercially available fuel consumption display and recording device to use in their personal vehicle for two months. For the first month the display is blank as the device records a baseline of driving and fuel consumption. For the second month the display is switched on to show drivers one of three feedback designs. This paper presents preliminary results (N=36) of a larger study that will include 150 drivers along the California-Nevada Interstate-80 corridor. Using a mixed-effects linear model, an average decrease of 13 between 2% and 8% in fuel consumption (gallons/100 miles) between the without- and with-feedback months, depending on the feedback designs, is found. Categorizing trips into types based on distance and multiple speed characteristics, there are differences in the apparent effectiveness of feedback across trip types. Most trips average approximately 5% reduction in fuel consumption. The long distance highway trip type showed only a 1% decrease in fuel consumption between the two study periods

Goal Setting, Framing, and Anchoring Responses to Ecodriving Feedback

Ecodriving, defined here as the adoption of energy efficient driving styles and practices (primarily moderating acceleration, top speed, increased coasting, and improved maintenance practices), has long been recognized as a potential source of reductions in transportation energy use. Estimates of energy savings attributed to ecodriving range widely, from less than 5% to as high as 20% depending on the driving and experimental context. To explore the effects on ecodriving of interaction between drivers and in-vehicle energy feedback, a customized, interactive energy feedback interface was deployed in a field test with real-world drivers. This paper presents the results of interviews with 46 Plug-in Hybrid Electric Vehicle (PHEV) drivers who were given the ecodriving feedback interface for a multi-week trial including an interface off (baseline) and on (treatment) condition. This paper relies specifically on self-reports of driver motivations and behaviors to better understand what types of information motivated new ecodriving behavior; a future paper will investigate quantitative fuel consumption effects. Driver interviews at the conclusion of the study revealed that the introduction of feedback led three fourths of drivers to change driving styles to maximize on-road efficiency, at least in the short term. In addition, this study finds that the context of the feedback information, provided by a built-in goal or other contextualizing information such as a comparison value, is important for both comprehension and motivation. Personalization of the information allowed different drivers to access pertinent information, increasing the motivational value of the information. Instantaneous performance feedback such as real-time energy economy or power is used primarily for experimentation and learning of new ecodriving behaviors, whereas average performance feedback is used primarily for goal-setting and goal achievement. In addition, the direct comparison of personalized driver goals and average performance created a game-like experience that encouraged high achievement. Finally, the driver interviews revealed that feedback frames driving as a time to act in an efficient manner

Carsharing and the Built Environment: A GIS-Based Study of One U.S. Operator

The use of carsharing vehicles over a period of 16 months in 2006-07 was compared to built environment and demographic factors in this GIS-based multivariate regression study of an urban U.S. carsharing operator. Carsharing is a relatively new transportation industry in which companies provide members with short-term vehicle access from distributed neighborhood locations. The number of registered carsharing members in North America has doubled every year or two to a current level of approximately 320,000. Researchers have long supposed that public transit access is a key factor driving demand for carsharing. The results of this study, however, find an ambiguous relationship between the activity at carsharing locations and public transit access. Light rail availability is found to have a significant and positive relationship to carsharing demand. Regional rai! l availability is found to be weakly and negatively associated with carsharing demand, although limitations in the available data make it impossible to ascribe the observed difference to user demand, random variation, or other factors specific to the industry

Carsharing and the Built Environment

The use of carsharing vehicles over a period of 16 months in 2006-07 was compared to built environment and demographic factors in this GIS-based multivariate regression study of an urban U.S. carsharing operator. Carsharing is a relatively new transportation industry in which companies provide members with short-term vehicle access from distributed neighborhood locations. The number of registered carsharing members in North America has doubled every year or two to a current level of approximately 320,000. Researchers have long supposed that public transit access is a key factor driving demand for carsharing. The results of this study, however, find an ambiguous relationship between the activity at carsharing locations and public transit access. Light rail availability is found to have a significant and positive relationship to carsharing demand. Regional rail availability is found to be weakly and negatively associated with carsharing demand, although limitations in the available data make it impossible to ascribethe observed difference to user demand, random variation, or other factors specific to the industry

Carsharing and the Built Environment: A GIS-Based Study of One U.S. Operator

The use of carsharing vehicles over a period of 16 months in 2006-07 was compared to built environment and demographic factors in this GIS-based multivariate regression study of an urban U.S. carsharing operator. Carsharing is a relatively new transportation industry in which companies provide members with short-term vehicle access from distributed neighborhood locations. The number of registered carsharing members in North America has doubled every year or two to a current level of approximately 320,000. Researchers have long supposed that public transit access is a key factor driving demand for carsharing. The results of this study, however, find an ambiguous relationship between the activity at carsharing locations and public transit access. Light rail availability is found to have a significant and positive relationship to carsharing demand. Regional rai! l availability is found to be weakly and negatively associated with carsharing demand, although limitations in the available data make it impossible to ascribe the observed difference to user demand, random variation, or other factors specific to the industry.UCD-ITS-RR-08-41, Civil Engineering